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Feature extraction from optimal time-frequency and time-scale transforms for the classification of the knee joint vibroarthrographic signals

Eskandari, H ; Sharif University of Technology | 2003

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  1. Type of Document: Article
  2. DOI: 10.1109/ISSPIT.2003.1341219
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2003
  4. Abstract:
  5. In this study knee joint vibroarthrographic (VAG) signals are recorded during active knee movements, which are essentially non-stationary. Because of this nature, common frequency methods are unable to represent the signals, accurately. Both time-frequency and time-scale transforms are used in this research which are good tools for studying non-stationary signals. By optimizing the utilized transforms, it was concluded that the wavelet packet, having the ability of multiresolutional analysis, is a more promising method to extract features from the VAG signals. The performance of different feature extraction techniques were compared by using three new recorded and extensive databases, arranged especially for the purpose of this research. © 2003 IEEE
  6. Keywords:
  7. Feature extraction ; Knee ; Optimization methods ; Signal analysis ; Signal resolution ; Spatial databases ; Time frequency analysis ; Wavelet analysis ; Wavelet packets ; Wavelet transforms
  8. Source: 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003, 14 December 2003 through 17 December 2003 ; 2003 , Pages 709-712 ; 0780382927 (ISBN); 9780780382923 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/1341219